AIMC Topic: Shoulder

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Combination Use of Compressed Sensing and Deep Learning for Shoulder Magnetic Resonance Imaging With Various Sequences.

Journal of computer assisted tomography Mar 9, 2023
OBJECTIVE: For compressed sensing (CS) to become widely used in routine magnetic resonance imaging (MRI), it is essential to improve image quality. This study aimed to evaluate the usefulness of combining CS and deep learning-based reconstruction (DL...
Magnetic Resonance Imaging Shoulder Shoulder Joint Retrospective Studies Deep Learning Humans
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Magnetic resonance shoulder imaging using deep learning-based algorithm.

European radiology Feb 24, 2023
OBJECTIVE: To investigate the feasibility of deep learning-based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI).
Retrospective Studies Deep Learning Magnetic Resonance Imaging Humans Algorithms Shoulder Magnetic Resonance Spectroscopy
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Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

European radiology Feb 18, 2023
OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR im...
Signal-To-Noise Ratio Cartilage, Articular Shoulder Pain Image Enhancement Shoulder Adult Humans Image Processing, Computer-Assisted Deep Learning Middle Aged Magnetic Resonance Imaging Female Young Adult
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The assistance of BAZAR robot promotes improved upper limb motor coordination in workers performing an actual use-case manual material handling.

Ergonomics Jan 26, 2023
This study aims at evaluating upper limb muscle coordination and activation in workers performing an actual use-case manual material handling (MMH). The study relies on the comparison of the workers' muscular activity while they perform the task, wit...
Robotics Shoulder Upper Extremity Posture Muscle, Skeletal Female Male Humans
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Deep Learning Diagnosis and Classification of Rotator Cuff Tears on Shoulder MRI.

Investigative radiology Jan 18, 2023
BACKGROUND: Detection of rotator cuff tears, a common cause of shoulder disability, can be time-consuming and subject to reader variability. Deep learning (DL) has the potential to increase radiologist accuracy and consistency.
Shoulder Rotator Cuff Deep Learning Magnetic Resonance Imaging Rotator Cuff Injuries Humans
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MR imaging for shoulder diseases: Effect of compressed sensing and deep learning reconstruction on examination time and imaging quality compared with that of parallel imaging.

Magnetic resonance imaging Aug 5, 2022
PURPOSE: To compare capabilities of compressed sensing (CS) with and without deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) with and without DLR for improving examination time and image quality of shoulder MRI for...
Signal-To-Noise Ratio Humans Deep Learning Magnetic Resonance Imaging Artifacts Shoulder
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Measuring the critical shoulder angle on radiographs: an accurate and repeatable deep learning model.

Skeletal radiology Mar 28, 2022
PURPOSE: Since the critical shoulder angle (CSA) is considered a risk factor for shoulder pathology and the intra- and inter-rater variabilities in its calculation are not negligible, we developed a deep learning model that calculates it automaticall...
Retrospective Studies Deep Learning Shoulder Shoulder Joint Radiography Humans
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Convolutional LSTM: a deep learning approach to predict shoulder joint reaction forces.

Computer methods in biomechanics and biomedical engineering Mar 2, 2022
We developed a Convolutional LSTM (ConvLSTM) network to predict shoulder joint reaction forces using 3D shoulder kinematics data containing 30 different shoulder activities from eight human subjects. We considered simulation outcomes from the AnyBody...
Shoulder Joint Deep Learning Muscle, Skeletal Shoulder Humans Computer Simulation
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Combined Feedback Feedforward Control of a 3-Link Musculoskeletal System Based on the Iterative Training Method.

BioMed research international Nov 8, 2021
The investigation and study of the limbs, especially the human arm, have inspired a wide range of humanoid robots, such as movement and muscle redundancy, as a human motor system. One of the main issues related to musculoskeletal systems is the joint...
Movement Models, Anatomic Artifacts Shoulder Muscle, Skeletal Torque Humans Algorithms Elbow Robotics Arm Machine Learning Feedback Models, Theoretical
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The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.

Scientific reports Jan 15, 2021
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...
Shoulder X-Rays Radiographic Image Interpretation, Computer-Assisted Wrist Humans Fractures, Bone Area Under Curve Elbow Neural Networks, Computer ROC Curve
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